ReviewHuman molecular genetics2018
Electronic health records: the next wave of complex disease genetics.
Review in Human molecular genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
38 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Global Biobank Meta-analysis Initiative: How can global health benefit by its use?Journal of global health · 2023Pooled it
- Glaucoma Genetic Risk Scores in the Million Veteran Program.Ophthalmology · 2022Pooled it
- Association study in African-admixed populations across the Americas recapitulates asthma risk loci in non-African populations.Nature communications · 2019Pooled it
- A simple approach for multiple observations improves power to detect genetic effects and genomic prediction accuracy.HGG advances · 2026Article
- Inclusion bias affects common variant discovery and replication in a health-system linked biobank.American journal of human genetics · 2026Article
- SAIGE-GPU: accelerating genome- and phenome-wide association studies using GPUs.Bioinformatics (Oxford, England) · 2026Article
- Laboratory and genetic characteristic associated with gallbladder-related outcomes in sickle cell disease in Brazil: results from the REDS-III multicenter cohort study.Annals of hematology · 2026Article
- Liability threshold model-based disease risk prediction based on electronic health record phenotypes.Nature genetics · 2025Article
- A simple approach for multiple observations improves power to detect genetic effects and genomic prediction accuracy.medRxiv : the preprint server for health sciences · 2025Article
- Implications of the choice of method to identify major depressive disorder in large research cohorts.Journal of mood and anxiety disorders · 2025Article
- Expanding scope of genetic studies in the era of biobanks.Human molecular genetics · 2025Article
- Implications of gene × environment interactions in post-traumatic stress disorder risk and treatment.The Journal of clinical investigation · 2025Review
- Clinical associations with treatment resistance in depression: An electronic health record study.Psychiatry research · 2024Article
- Algorithms for the identification of prevalent diabetes in the All of Us Research Program validated using polygenic scores.Scientific reports · 2024Article
- Clinical and genetic contributions to medical comorbidity in bipolar disorder: a study using electronic health records-linked biobank data.Molecular psychiatry · 2024Article
- Characterising the genetic architecture of changes in adiposity during adulthood using electronic health records.Nature communications · 2024Article
- Accelerating Genome- and Phenome-Wide Association Studies using GPUs - A case study using data from the Million Veteran Program.bioRxiv : the preprint server for biology · 2024Article
- Review
- Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease.Cell genomics · 2022Article
- A research agenda to support the development and implementation of genomics-based clinical informatics tools and resources.Journal of the American Medical Informatics Association : JAMIA · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
The combination of electronic health records (EHRs) with genetic data has ushered in the next wave of complex disease genetics. Population-based biobanks and other large cohorts provide sufficient sample sizes to identify novel genetic associations across the hundreds to thousands of phenotypes gleaned from EHRs. In this review, we summarize the current state of these EHR-linked biobanks, explore ongoing methods development in the field and highlight recent discoveries of genetic associations. We enumerate the many existing biobanks with EHRs linked to genetic data, many of which are available to researchers via application and contain sample sizes >50 000. We also discuss the computational and statistical considerations for analysis of such large datasets including mixed models, phenotype curation and cloud computing. Finally, we demonstrate how genome-wide association studies and phenome-wide association studies have identified novel genetic findings for complex diseases, specifically cardiometabolic traits. As more researchers employ innovative hypotheses and analysis approaches to study EHR-linked biobanks, we anticipate a richer understanding of the genetic etiology of complex diseases.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.